Method and apparatus for video encoding and decoding using bi-prediction

ABSTRACT

Different implementations are described, particularly implementations for video encoding and decoding using motion compensation with bi-prediction are presented. The encoding method comprises for a picture, obtaining a first predictor for a block of the picture using a first reference picture; obtaining a second predictor for said block of the picture using a second reference picture; using the first predictor and the second predictor for forming a third predictor for the block in bi-prediction inter prediction, wherein the third predictor is obtained as a weighted average of the first predictor and the second predictor; and wherein a weight used in the weighed prediction depend on the position of the sample in the block. Ohers embodiments are presented for implementing block triangle partition prediction, for implementing block partition prediction using multiple patterns and for corresponding motion compensation in decoding method.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. Serial No. 17/277953 (nowU.S. Pat. No. ______) which was the national stage entry under 35 U.S.C.§371 of International Application PCT/US2019/051653, filed Sep. 18,2019, which claims the benefit of European Patent Application No.18306231.4, filed Sep. 21, 2018, the contents of each of which arehereby incorporated by reference in their entireties.

BACKGROUND

The technical field of the one or more implementations is generallyrelated to video compression. To achieve high compression efficiency,image and video coding schemes usually employ prediction and transformto leverage spatial and temporal redundancy in the video content.Generally, intra or inter prediction is used to exploit the intra orinter frame correlation, then the differences between the original blockand the predicted block, often denoted as prediction errors orprediction residuals, are transformed, quantized, and entropy coded. Toreconstruct the video, the compressed data are decoded by inverseprocesses corresponding to the entropy coding, quantization, transform,and prediction. In the HEVC video compression standard, also known asrecommendation ITU-T H.265, the bi-prediction process used in interprediction comprises the averaging of 2 uni-directional predictionsignals. FIG. 1 illustrates the bi-prediction process in HEVC. Theaveraging of the 2 uni-directional prediction is done at a higherprecision than either the input bitdepth or internal bitdepth as shownin FIG. 1 . The bi-prediction formula is shown in Equation 1, whereoffset and shift are used to normalize the final predictor to inputbit-depth :

$\begin{matrix}{P_{bidir} = \left( {P_{L0} + P_{L1} + offset} \right) \gg shift} & \text{­­­Equation 1}\end{matrix}$

As there is no rounding in intermediate stages, HEVC interpolationfilter allows certain implementation optimizations.

Recent additions to video compression technology include variousindustry standards, versions of the reference software and/ordocumentations such as Joint Exploration Model (JEM) and later VTM(Versatile Video Coding (WC) Test Model) being developed by the JVET(Joint Video Exploration Team) group. The aim is to make furtherimprovements to the existing HEVC (High Efficiency Video Coding)standard. For instance, in more recent approach of video codec, multipleweights are used for averaging 2 uni-directional prediction to get abi-directional prediction. Typically, the weights used are { -¼, 5/4},{⅜, ⅝} or {½, ½} ({½, ½} being the one implemented in HEVC), and thebi-prediction formula is modified as in Equation 2. Only one weight isused for the entire block.

$\begin{matrix}{P_{bidir} = \left( {\left( {1 - w_{1}} \right) \ast P_{L0} + w_{1} \ast P_{L1} + offset} \right) \gg shift} & \text{­­­Equation 2}\end{matrix}$

In another approach of video codec, triangular prediction is used inmerge mode. FIG. 2 illustrates the splitting of a coding unit CU intotwo triangular prediction units. As shown in FIG. 2 , a CU is split intotwo triangular prediction units PU0 and PU1, either in diagonal orinverse diagonal direction along a diagonal edge. Each triangularprediction unit in the CU is inter-predicted using its own motionvectors and reference frame index which are derived from a mergecandidate list. In this context, an adaptive weighting process isapplied to the diagonal or inverse diagonal edge between the twotriangular prediction units to derive the final prediction for the wholeCU. FIG. 3 illustrates such weighting process on the diagonal edgebetween the two triangular prediction units. The triangular predictionunit mode is only applied to CUs in skip or merge mode. When thetriangular prediction unit mode is applied to the CU, an indexindicating the direction of splitting the CU into two triangularprediction units and the motion vectors of the two triangular predictionunits are signaled. A common list of 5 uni-directional predictors isderived for both Prediction Units, same spatial and temporal positionsare checked than in classical merge process but only uni-directionalvectors are used. Redundant motion vectors are not added to the list andzero motion vectors are added at the end of the list if there is notenough candidates. The number of motion vector predictor is 5 for agiven prediction unit, 20 combinations are tested for each diagonal(5*4=20, the same motion vector predictor cannot be used for both PUs).The index ranges from 0 to 39 and a look-up table, see Error! Referencesource not found., is used for deriving splitting direction and motionvectors for each PU from the index. The first element of a given tripletgives the diagonal direction, the second and third elements giverespectively the predictor index for PU0 and PU1 respectively. The indexsyntax is shown in Error! Reference source not found. (e.g., trianglepartitions and corresponding merge index syntax).

TABLE 1 prediction_unit( x0, y0, nPbW, nPbH ) { Descriptor  if( cu_skip_flag[ x0 ][ y0 ] ) {       triangle_flag[ x0 ][ y0]    if( MaxNumMergeCand > 1 ) {       if( triangle_flag[ x0 ][ y0] ) {        triangle_merge_data( x0, y0, nPbW, nPbH) ae(v)       } else {        merge_idx[ x0 ][ y0 ]       }        } else { /* MODE_INTER */    merge_flag[ x0 ][ y0 ] ae(v)     if( merge_flag[ x0 ][ y0 ] ) {      if( MaxNumMergeCand > 1 ) {        if( triangle_flag[ x0 ][ y0] ) {          triangle_merge_data( x0, y0, nPbW, nPbH)         } else {          merge_idx[ x0 ][ y0 ] ae(v)         }       }     } }triangle_merge_data( x0, y0, nPbW, nPbH) {  most_probable_idx[ x0 ][ y0 ] u(1)  if( most_probable_idx[ x0 ][ y0 ] ) {     zero_or_one_idx[ x0 ][ y0 ]u(1)   } else {     remaining_idx[ x0 ][ y0 ] se(v)   } }

TABLE 2 is a look-up table to determine diagonal direction andpredictors.

TABLE 2 const uint8_t g_TriangleCombination[TRIANGLE_MAX_NUM_CANDS][3] ={ { 0, 1, 0 }, { 1, 0, 1 }, { 1, 0, 2 }, { 0, 0, 1 }, { 0, 2, 0 }, { 1,0, 3 }, { 1, 0, 4 }, { 1, 1, 0 }, { 0, 3, 0 }, { 0, 4, 0 }, { 0, 0, 2 },{ 0, 1, 2 }, { 1, 1, 2 }, { 0, 0, 4 }, { 0, 0, 3 }, { 0, 1, 3 }, { 0, 1,4 }, { 1, 1, 4 }, { 1, 1, 3 }, { 1, 2, 1 }, { 1, 2, 0 }, { 0, 2, 1 }, {0, 4, 3 }, { 1, 3, 0 }, { 1, 3, 2 }, { 1, 3, 4 }, { 1, 4, 0 }, { 1, 3, 1}, { 1, 2, 3 }, { 1, 4, 1 }, { 0, 4, 1 }, { 0, 2, 3 }, { 1, 4, 2 }, { 0,3, 2 }, { 1, 4, 3 }, { 0, 3, 1 }, { 0, 2, 4 }, { 1, 2, 4 }, { 0, 4, 2 },{ 0, 3, 4 }, }

FIG. 4 illustrates sub-block motion vector storage for trianglepartitions according to a particular compression scheme. In animplementation, motion vectors are stored for each 4✕4 sub-blocks. WhenTriangle partitions are used for a CU, the motion vectors used for eachpartition are stored in the same manner for each sub-blocks, but forsub-blocks on the edge, only the motion vector from one PU is stored, asshown in FIG. 4 .

The bi-prediction of inter coded blocks in combination with triangularpartitions raises implementation issues. A less computational method forbi-prediction is therefore desirable. Accordingly, several embodimentsare disclosed to improve bi-prediction of inter coded blocks.

SUMMARY

According to an aspect of the present disclosure, a method for encodinga picture is disclosed. Such a method comprises obtaining a firstpredictor for a block of the picture using a first reference picture;obtaining a second predictor for the block of the picture using a secondreference picture; using the first predictor and the second predictorfor forming a third predictor for the block of the picture inbi-prediction inter prediction, wherein the third predictor is obtainedas a weighted average of the first predictor and the second predictor;and wherein a sample of the third predictor is obtained by applying afirst weight to a sample of the first predictor and by applying a secondweight to a sample of the second predictor; the sample of the thirdpredictor, the sample of the first predictor and the sample of thesecond predictor sharing a same position in the block; and the firstweight and the second weight depending on the position of the sample inthe block.

According to another aspect of the present disclosure, an apparatus forencoding a picture is disclosed. Such an apparatus comprises means forobtaining a first predictor for a block of the picture using a firstreference picture; means for obtaining a second predictor for the blockof the picture using a second reference picture; means for forming athird predictor for the block of the picture in bi-prediction interprediction using the first predictor and the second predictor, whereinthe third predictor is obtained as a weighted average of the firstpredictor and the second predictor; and wherein a sample of the thirdpredictor is obtained by applying a first weight to a sample of thefirst predictor and by applying a second weight to a sample of thesecond predictor; the sample of the third predictor, the sample of thefirst predictor and the sample of the second predictor sharing a sameposition in the block; and the first weight and the second weightdepending on the position of the sample in the block..

According to an aspect of the present disclosure, an apparatus forencoding a picture is provided, the apparatus including a processor, andat least one memory coupled to the processor, the processor beingconfigured to implement any variants of the encoding the method.

According to another aspect of the present disclosure, a method fordecoding a video is disclosed. Such a method comprises receiving in abitstream coded video data and for motion compensation, obtaining afirst predictor for a block of the picture using a first referencepicture; obtaining a second predictor for the block of the picture usinga second reference picture; using the first predictor and the secondpredictor for forming a third predictor for the block of the picture inbi-prediction inter prediction, wherein the third predictor is obtainedas a weighted average of the first predictor and the second predictor;and wherein a sample of the third predictor is obtained by applying afirst weight to a sample of the first predictor and by applying a secondweight to a sample of the second predictor; the sample of the thirdpredictor, the sample of the first predictor and the sample of thesecond predictor sharing a same position in the block; and wherein thefirst weight and the second weight depend on the position of the samplein the block.

According to another aspect of the present disclosure, an apparatus fordecoding a video is disclosed. Such an apparatus comprises means forreceiving in a bitstream coded video data and means for processingmotion compensation, said means for processing motion compensationfurther comprising means for obtaining a first predictor for the blockof a picture using a first reference picture; means for obtaining asecond predictor for the block of the picture using a second referencepicture; means for forming a third predictor for the block of thepicture in bi-prediction inter prediction using the first predictor andthe second predictor, wherein the third predictor is obtained as aweighted average of the first predictor and the second predictor;wherein a sample of the third predictor is obtained by applying a firstweight to a sample of the first predictor and by applying a secondweight to a sample of the second predictor; the sample of the thirdpredictor, the sample of the first predictor and the sample of thesecond predictor sharing a same position in the block; and wherein thefirst weight and the second weight depend on the position of the samplein the block.

According to an aspect of the present disclosure, an apparatus fordecoding a video is provided, the apparatus including a processor, andat least one memory coupled to the processor, the processor beingconfigured to receive in a bitstream coded video data and to implementany variants of the decoding the method.

The present disclosure also provides a signal comprising video datagenerated according to the method or the apparatus of any of thepreceding descriptions. The present embodiments also provide a computerprogram product including instructions, which, when executed by acomputer, cause the computer to carry out the methods described.

The present disclosure also provides a computer readable storage mediumhaving stored thereon a bitstream generated according to the methodsdescribed above. The present disclosure also provides a method andapparatus for transmitting the bitstream generated according to themethods described above.

The above presents a simplified summary of the subject matter in orderto provide a basic understanding of some aspects of subject matterembodiments. This summary is not an extensive overview of the subjectmatter. It is not intended to identify key/critical elements of theembodiments or to delineate the scope of the subject matter. Its solepurpose is to present some concepts of the subject matter in asimplified form as a prelude to the more detailed description that ispresented later.

Additional features and advantages of the present disclosure will bemade apparent from the following detailed description of illustrativeembodiments which proceeds with reference to the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates bi-prediction process according to the HEVC standard;

FIG. 2 illustrates the splitting of a coding unit CU into two triangularprediction units according to a particular compression scheme;

FIG. 3 illustrates weighting process on the diagonal edge between thetwo triangular prediction units according to a particular compressionscheme;

FIG. 4 illustrates sub-block motion vector storage for trianglepartitions according to a particular compression scheme;

FIG. 5 illustrates the motion compensation process for bi-predictedtriangular partitions according to a particular compression scheme;

FIG. 6 illustrates the motion compensation process for uni-predictedtriangular partitions according to a particular compression scheme;

FIG. 7 illustrates an example of a modified motion compensation processadapted to triangular prediction according to an embodiment of thepresent disclosure;

FIG. 8 illustrates examples of multiple diagonal patterns according toan embodiment of the present disclosure;

FIG. 9 and FIG. 10 illustrate other examples of multiple patternsaccording to an embodiment of the present disclosure;

FIG. 11 illustrates an embodiment of a proposed motion vector storage;

FIG. 12 illustrates an exemplary encoder according to an embodiment ofthe present disclosure;

FIG. 13 illustrates an exemplary decoder according to an embodiment ofthe present disclosure;

FIG. 14 illustrates a block diagram of an example of a system, in whichvarious aspects and embodiments are implemented; and

FIG. 15 illustrates a weighting bi prediction implemented in any of adecoding method or encoding method according to an embodiment of thepresent disclosure.

DETAILED DESCRIPTION

A method and an apparatus for encoding a video into a bitstream aredisclosed. A corresponding decoding method and apparatus are furtherdisclosed. At least some embodiments further relate to the bi-predictionfor inter coded blocks in a video compression scheme. It is to beunderstood that the figures and descriptions have been simplified toillustrate elements that are relevant for a clear understanding of thepresent principles, while eliminating, for purposes of clarity, manyother elements found in typical encoding and/or decoding devices. Itwill be understood that, although the terms first and second may be usedherein to describe various elements, these elements should not belimited by these terms. These terms are only used to distinguish oneelement from another.

The various embodiments are described with respect to theencoding/decoding of a picture. They may be applied to encode/decode apart of picture, such as a slice or a tile, or a whole sequence ofpictures.

Various methods are described above, and each of the methods comprisesone or more steps or actions for achieving the described method. Unlessa specific order of steps or actions is required for proper operation ofthe method, the order and/or use of specific steps and/or actions may bemodified or combined.

At least some embodiments relate to method for video encoding or videodecoding comprising weighted bi-prediction wherein the weights of theweighted bi-prediction are dependent on the position of the sample inthe block of a picture of the encoded or decoded video.

A first problem of weighted motion compensation for bi-predictedtriangular partitions, is that each PU is bi-predicted, thus involving aweighting process on the edge between the 2 predictions. FIG. 5illustrates the motion compensation process for bi-predicted triangularpartitions. For the samples on the edge as illustrated on FIGS. 3, 4motion compensations are needed as shown in FIG. 5 . A lesscomputational method is therefore desirable.

A first solution has been proposed that restricts triangular PU touni-prediction to decrease the memory bandwidth. FIG. 6 illustrates themotion compensation process for uni-predicted triangular partitions. Inthis case, the motion compensation process is simplified as shown inFIG. 6 . However, this solution can still benefit from improvementregarding the precision of the process. At least one embodiment relatesto improving the precision of the bi-prediction process of inter codedblocks.

In an enhancement of bi-predicted triangular partitions, it is desirableto improve the compression efficiency by adding more patterns. Then, asecond problem of weighted motion compensation for bi-predictedpartitions is to signal the added patterns without having a large costof coding the index of the combination of partitions and motion vectors.At least one embodiment relates to improving the signaling of thebi-prediction process of inter coded blocks.

A third problem is the storage of the motion vectors used for each PU inthe subblocks on the edge. For the sample on the edge, a weighting isdone between the 2 predictions, this means that at least 2 motionvectors are used to predict this sample, but in memory only the motionvector used to predict the current PU is stored, this may lead tosuboptimal motion propagation with the neighboring blocks. At least oneembodiment relates to improving the storage of motion vectors for thebi-prediction process of inter coded blocks.

Accordingly, several embodiments are disclosed to improve thebi-prediction of inter coded blocks.

Generic Embodiment

At least one embodiment of a generic method for weighted bi-prediction1500 is illustrated in FIG. 15 . Such method is easily implemented inany one of motion compensation process of a method for video encoding ora method for video decoding by the skilled in the art wherein theobtaining of input information is determined in a RDO loop in anencoding method or decoded from received data in a decoder. According tothe present principles, the weights of the weighted bi-prediction aredependent on the position of the sample in the block of a picture of theencoded or decoded video. Thus, processing of triangular partition isadvantageously performed as a weighted prediction and results into anincreased precision of the bi-prediction process of inter coded blocksas will be explained.

First, at 1510 of FIG. 15 , a first predictor and a second predictor areobtained for a block of a picture to be encoded/decoded. The firstpredictor for the block uses a first reference picture stored in a listL0 and the second predictor for the block uses a second referencepicture stored in list L1. Those 2 uni-directional predictors arecombined to form a third predictor by bi-directional inter prediction.

According to different embodiments described hereafter, at 1520 at leastone information is obtained that is used in the determining of positiondependents weights. This step is optional. According to non-limitingembodiments, a first information indicates the splitting of the block ofthe picture with a triangular partition, a second information indicatesthe direction of the edge the triangular partition of the block, a thirdinformation indicates the position of the edge of the triangularpartition. According to another embodiment, the splitting of the blockis not limited to triangular partition and more generic splitting of ablock in 2 partitions along an edge as illustrated on FIG. 9 . Then, aninformation used in the determining of position dependents weights is aninformation that indicates the splitting of the block of the picturewith an edge partition. According to non-limiting embodiments, a fourthinformation indicates that an edge of the so-called “triangularpartition” is vertical or horizontal (and not diagonal). According toanother embodiment, an information used in the determining of positiondependents weights is an information related to the color component. Thenumber of samples in a block may be different if the block is a lumablock or a chroma block, accordingly the weights are also determinedaccording to the color component. Besides that, the weights are alsodetermined according to the size of the block. According to anotherembodiment, the position dependent weights in bi-prediction are notlimited to triangle or edge partition, thus an information is moregenerally any information used in the determining of position dependentsweights.

As previously described, in a particular embodiment, multiple weightsare used for averaging 2 uni-directional prediction to get abi-directional prediction. According to non-limiting example, theweights used are { -¼, 5/4}, {⅜, ⅝} or {½, ½} where only one pair ofweights is used for the entire block. The present principles areadvantageously compatible with the selection of block-based weight amonga set of weights, wherein the position dependent weight of a sample isderived from the selected block-based weight. In other words, the weightof a sample is determined according to the position of the sample and tothe selected block-based weight of the predictor. Accordingly, at 1530,the selected block-based weight among a set of weights are optionallydetermined.

At 1540, the position dependent weight of a sample in the block isdetermined. According to particular embodiments, the position dependentweight of a sample in the block is further derived from at least one ofthe obtained information, the selected block-based weight, the componentof the block, the size of the block. A sample of the third predictor isobtained by applying a first weight to a sample of the first predictorand by applying a second weight to a sample of the second predictor.Thus, the first and second weights are determined depending on theposition of the sample in the block. The sample of the third predictor,the sample of the first predictor and the sample of the second predictorshare a same position in the block, the samples are co-located in theblock.

According to an embodiment, the position dependent weightsbi-directional inter-prediction is used for triangular prediction. Aseach triangular prediction unit is restricted to uni-prediction, thetriangular prediction is implemented as a bi-prediction wherein thefirst weight and second weight depends on the sample position. In thecase of triangular partition, the first weight and the second weightdepend on the distance between the sample and the edge of the triangularpartition of the block. However, the present principles are not limitedto triangle partitions and can be easily extended to other partitions ofthe block including horizontal/vertical edge and including multiplepatterns. Different variants and refinements are described hereafter.The position of the edge in the block used to compute weights isobtained from the at least one information indicating the splitting ofthe block into 2 partitions. Besides, in a variant, the at least oneinformation is signaled to allow a decoding method corresponding to theencoding method to use the same information for bi prediction. Forinstance, in an encoding method, the least one signaled information isentropy coded. For instance, in a decoding method, the least oneinformation is obtained from entropy decoding of the signaledinformation.

However, the position dependent weights in bi-prediction are not limitedto triangle or edge partition. For instance, the present principles arealso compatible with avec Combined Inter-Intra Prediction whereinweights depend on sample location without other partition.

Once the sample dependent weights are obtained, at 1550, thebi-prediction process is processed. The third predictor, also referredto as the bi-directional predictor, is obtained as a weighted average ofthe first predictor and the second predictor. Advantageously, theweighted average is processed on an increased bit-depth compared to thebit-depth of the predictors. Then, at 1560, the weighted average on thelarger bit-depth is shifted and clipped to obtain the third predictor onthe same bit-depth as the first and second predictor.

At 1570, the bi prediction ends and the third predictor for the coded ordecoded block of image is output.

Embodiment 1

At least one embodiment of the encoding or decoding method thus relatesto the weighting of samples on the edge of a triangular partition withincreased precision. FIG. 7 illustrates an example of a modified motioncompensation process for triangular prediction according to anembodiment. As each triangular prediction unit is restricted touni-prediction, a bi-prediction with sample position-dependent weightingfactors is processed to obtain the triangular prediction. This modifiedmotion compensation process in which the weight used for averaging 2uni-prediction P₁ and P₂ may be different for each sample is implementedwith the position dependent weights illustrated on FIGS. 3 and 4 . Theweight depends on the distance between the current sample S₀, S₁, S₂ orS₃ and the edge of between the 2 triangular Pus P₁ and P₂. For instance,the first weight W₁ is equal to 4/8 and second weight W₂is equal to 4/8for a sample S₀ on the edge of partition. For instance, the first weightW₁ is equal to ⅛ and second weight W₂ is equal to ⅞ for a sample S₁distant from the edge of partition. Reversely, the first weight W₁ isequal to ⅞ and second weight W₂is equal to ⅛ for a sample S₂ at the samedistance from the edge of partition. And, the first weight W₁ is equalto 8/8 and second weight W₂ is equal to 0/8 when the distance betweenthe sample S₃ and the edge of partition is above a defined value. Asillustrated on FIG. 7 , the shifting to input bitdepth and clipping areadvantageously postponed after the weighting of the samples, thusbeneficing extended precision. In this embodiment, a first informationindicating the splitting of the block of the picture with a triangularpartition for instance according to the direction Top Left to BottomRight as shown on FIG. 3 . For instance, a dedicated syntax, such astriangle_flag, is used to indicate the triangle partitioning of theblock. In a block of size NxN (for instance N= 8 as on FIG. 3 ) of theluma component, the weight W₁ at a location (x,y), x and y in the range[0, N-1], in the block is for instance obtained by Equation 3:

$\begin{matrix}{\text{W}_{1} = \left( {\text{Clip}\left( {0,8,\left( {\text{x} - \text{y}} \right) + 4} \right)\text{and W}_{2} = 8\text{- W}_{1}} \right)} & \text{­­­Equation (3)}\end{matrix}$

The resulting weights are in the range [0-8], thus, increased precisionis obtained for the weighting sum and followed by shifting and clippingoperation to reduce bit depth to the bit depth of the third predictor.As shown on FIG. 3 , the weight W₁ at a location (x,y) is different forchroma component.

Embodiment 2

At least one embodiment of the encoding or decoding method furtherrelates to the weighting of samples on the edge of a triangularpartition adapted to multiple partition patterns. Advantageously, aninformation indicating the arrangement of the multiple partitionpatterns is used to determine the edge in the block of the differentpartition patterns. Thus, the position of the sample in the block withrespect to the edge, for instance the distance, is determined. FIG. 8illustrates examples of multiple diagonal patterns according to anembodiment. Such multiple diagonal patterns wherein 2 (TL2BR or TR2BL)or more (TL2BR_1_4, TL2BR_3_4, TR2BL_1_4, TR2BL_3_4) patterns aredefined are desirable improve the coding efficiency. For instance, asshown on FIG. 8 , the diagonal may be shifted (by ¼ or ¾) rotated (TopLeft to Bottom Right TL2BR or Top Right to Bottom Left TR2BL).

At least one embodiment relates to bi-prediction with multiplepartitions such as triangular partitions. According to a variantcharacteristic, the coding of the multiple patterns and the index formotion vectors predictors are separated. Indeed, if 6 patterns from FIG.8 are implemented as bi-pred triangle partitions, 6*20=180 combinationswould have to be tested at the encoder. Various encoder speed-upimplementations are described below in variants of embodiment 5.

Accordingly, a dedicated syntax is described which separate thesignaling of the pattern using the syntax element diagonal_dir[x0][y0],diagonal_pos[x0][y0] from the signaling of motion vector index in themotion vector candidate list most_probable_idx. Thus, the secondinformation indicating the direction of the edge the triangularpartition of the block is diagonal_dir[x0][y0] syntax element, and thethird information indicating the position of the edge of the triangularpartition is the diagonal_pos[x0][y0] syntax element. Such syntaxelements are entropy coded, respectively decoded, and a binarization isproposed in TABLES 4 and 5. TABLE 1 shows a modified syntax for multiplepatterns.

TABLE 3 prediction_unit( x0, y0, nPbW, nPbH ) { Descriptor  if( cu_skip_flag[ x0 ][ y0 ] ) {       triangle_flag[ x0 ][ y0]    if( MaxNumMergeCand > 1 ) {       if( triangle_flag[ x0 ][ y0] ) {        triangle_merge_data( x0, y0, nPbW, nPbH) ae(v)       } else {        merge_idx[ x0 ][ y0 ]       }     }   } else { /* MODE_INTER */    merge_flag[ x0 ][ y0 ] ae(v)     if( merge_flag[ x0 ][ y0 ] ) {      if( MaxNumMergeCand > 1 ) {        if( triangle_flag[ x0 ][ y0] ) {          triangle_merge_data( x0, y0, nPbW, nPbH)         } else {          merge_idx[ x0 ][ y0 ] ae(v)         }       }     } }triangle_merge_data( x0, y0, nPbW, nPbH) {   diagonal_dir[ x0 ][ y0 ]u(1 )   diagonal_pos[ x0 ][ y0 ] ae(v)   most_probable_idx[ x0 ][ y0 ]u(1)   if( most_probable_idx[ x0 ][ y0 ] ) {    zero_or_one_idx[ x0 ][ y0 ] u(1)   } else {    remaining_idx[ x0 ][ y0 ] se(v)   } }

diagonal_dir[ x0 ][ y0 ] specifies the direction of the diagonal thatseparate the 2 prediction units of the block where x0, y0 specify thelocation ( x0, y0 ) of the top-left luma sample of the consideredprediction block relative to the top-left luma sample of the picture. Anexample of various diagonal directions is illustrated on FIG. 2 and alsoFIG. 8 . TABLE 4 shows binarization of the diagonal_dir syntax element.

TABLE 4 Value of diagonal_dir Name of diagonal_dir Bin string 0 TL2BR 01 TR2BL 1

diagonal_pos[ x0 ][ y0 ] specifies the position of the diagonal thatseparate the 2 prediction units of the block where x0, y0 specify thelocation ( x0, y0 ) of the top-left luma sample of the consideredprediction block relative to the top-left luma sample of the picture. Anexample of various diagonal positions is illustrated on FIG. 8 . TABLE 5shows binarization for the diagonal_pos syntax element.

TABLE 5 Value of diagonal_pos Name of diagonal_pos Bin string 0 TX2BX 01 TX2BX_1_4 10 2 TX2BX_3_4 11

Embodiment 3

In yet another variant, other edges may be used as horizontal, vertical,or edges from corner to middle of a block as shown in FIGS. 9 and 10 .For instance, FIG. 9 illustrates additional patterns where the edge iseither horizontal (HOR, HOR_1_4, HOR_3_4) or vertical (VER, VER_1_4,VER_3_4), and located at the middle (HOR, VER) or at one fourth(HOR_1_4, HOR_3_4, VER_1_4, VER_3_4) of the block. FIG. 10 illustratesyet additional patterns where the edge starts at the corner and ends atthe middle of a block. Of course, the partitions along an edgecompatible with the present principles are not limited to the describedpatterns, and the skilled in the art will easily apply the modifiedmotion compensation process using position dependent weighting factorsto other partition patterns. According to the present embodiment, thesyntax is modified to add the new patterns as shown in Error! Referencesource not found.. TABLE 6 is a proposed syntax for diagonal plushorizontal and vertical partitions.

TABLE 6 triangle_merge_data( x0, y0, nPbW, nPbH) {  diagonal_flag[ x0 ][ y0 ] u(1)   partition_dir[ x0 ][ y0 ] u(1)  partition_pos[ x0 ][ y0 ] ae(v)   most_probable_idx[ x0 ][ y0 ] u(1)  if( most_probable_idx[ x0 ][ y0 ] ) {     zero_or_one_idx[ x0 ][ y0 ]u(1)   } else {     remaining_idx[ x0 ][ y0 ] se(v)   } }

In another variant, a syntax element is coded that indicate otherweights to apply for the averaging on the edge.

Embodiment 4

The at least one embodiment is further well adapted to storage of motionvectors on the edge of the partition. In classical inter modes, whenbi-prediction is used, 2 motion vectors (1 for each list) is stored in4✕4 sub-blocks. In Triangle mode merge, in the variant where each PU isrestricted to uni-prediction, the 2 motion vectors used on the edge asshown in FIG. 11 , are advantageously stored in the respective 2 lists.Thus, the method is implemented at no extra cost. In combination withEquation 2, motion vectors may be stored with given weights w0 and w1for respectively motion vectors from List 0 and List 1. This allows abetter propagation of motion vectors hence a better prediction for theneighboring blocks.

Variants of Embodiment 5

Embodiment 5 relates to encoder speed-ups for motion compensation. Atthe encoder, the maximum number of tested combinations increases a lotwhen using more patterns, as for a given pattern, 20 combinations ofmotion vector predictors are used. For any combination, the averaging isprocessed in order to evaluate the candidate. At least one embodimentrelates to reducing the number of tested combinations. According to acharacteristic, by using a fast estimation with SATD (Sum of AbsoluteTransformed Differences), RDOQ (Rate Distortion optimized Quantization)process is done only for the best predictors.

In a first variant, the combinations that use a zero motion vectorpredictor added at the end of the list are not tested. For example ifpredictors 4 and 5 of the list are the added zero motion vectors, only3*2=6 combination for a given pattern are tested instead of 20. In thecase of 6 patterns 6*6=36 combinations are tested instead of 6*20=240.

In a second variant, the combinations that use motion vector selected inthe classical merge are tested, the other combinations are not tested.First, the best merge candidate for the classical merge is determined.One or 2 motion vector(s) depending if the best candidate isuni-directional or bi-directional are then recovered. If these motionvectors are in the list of motion vector predictors for Triangular PUs,then the test of possible combinations is reduced to the test ofcombinations that contains these motion vector predictors.

In a third variant, motion vector predictors are ranked with SAD orSATD. As all the combination are done using a maximum of 5 motion vectorpredictors, all 5 uni-directional motion vector predictors are rankedaccording their likelihood using SAD or SATD. The N (with N<5) bestsmotion vectors are kept or predictors superior to a threshold areremoved. Thus, the number of possible combinations is reduced.

Additional Embodiments and Information

This application describes a variety of aspects, including tools,features, embodiments, models, approaches, etc. Many of these aspectsare described with specificity and, at least to show the individualcharacteristics, are often described in a manner that may soundlimiting. However, this is for purposes of clarity in description, anddoes not limit the application or scope of those aspects. Indeed, allthe different aspects can be combined and interchanged to providefurther aspects. Moreover, the aspects can be combined and interchangedwith aspects described in earlier filings as well.

The aspects described and contemplated in this application can beimplemented in many different forms. FIGS. 12, 13 and 14 below providesome embodiments, but other embodiments are contemplated and thediscussion of FIGS. 12, 13 and 14 does not limit the breadth of theimplementations. At least one of the aspects generally relates to videoencoding and decoding, and at least one other aspect generally relatesto transmitting a bitstream generated or encoded. These and otheraspects can be implemented as a method, an apparatus, a computerreadable storage medium having stored thereon instructions for encodingor decoding video data according to any of the methods described, and/ora computer readable storage medium having stored thereon a bitstreamgenerated according to any of the methods described.

In the present application, the terms “reconstructed” and “decoded” maybe used interchangeably, the terms “pixel” and “sample” may be usedinterchangeably, the terms “image,” “picture” and “frame” may be usedinterchangeably. Usually, but not necessarily, the term “reconstructed”is used at the encoder side while “decoded” is used at the decoder side.

Various methods are described herein, and each of the methods comprisesone or more steps or actions for achieving the described method. Unlessa specific order of steps or actions is required for proper operation ofthe method, the order and/or use of specific steps and/or actions may bemodified or combined.

Various methods and other aspects described in this application can beused to modify modules, for example, the entropy coding 145, motioncompensation 170 and motion estimation 175 of a video encoder 100 asshown in FIG. 12 and entropy decoding 230 and motion compensation 275modules of a video decoder 200 FIG. 13 . Moreover, the present aspectsare not limited to VVC or HEVC, and can be applied, for example, toother standards and recommendations, whether pre-existing orfuture-developed, and extensions of any such standards andrecommendations (including VVC and HEVC). Unless indicated otherwise, ortechnically precluded, the aspects described in this application can beused individually or in combination.

Various numeric values are used in the present application, for example,the number of partitions or the value of the relative weights. Thespecific values are for example purposes and the aspects described arenot limited to these specific values.

FIG. 12 illustrates an encoder 100. Variations of this encoder 100 arecontemplated, but the encoder 100 is described below for purposes ofclarity without describing all expected variations.

Before being encoded, the video sequence may go through pre-encodingprocessing (101), for example, applying a color transform to the inputcolor picture (e.g., conversion from RGB 4:4:4 to YCbCr 4:2:0), orperforming a remapping of the input picture components in order to get asignal distribution more resilient to compression (for instance using ahistogram equalization of one of the color components). Metadata can beassociated with the pre-processing, and attached to the bitstream.

In the encoder 100, a picture is encoded by the encoder elements asdescribed below. The picture to be encoded is partitioned (102) andprocessed in units of, for example, CUs. Each unit is encoded using, forexample, either an intra or inter mode. When a unit is encoded in anintra mode, it performs intra prediction (160). In an inter mode, motionestimation (175) and compensation (170) are performed. The encoderdecides (105) which one of the intra mode or inter mode to use forencoding the unit, and indicates the intra/inter decision by, forexample, a prediction mode flag. Prediction residuals are calculated,for example, by subtracting (110) the predicted block from the originalimage block.

The prediction residuals are then transformed (125) and quantized (130).The quantized transform coefficients, as well as motion vectors andother syntax elements, are entropy coded (145) to output a bitstream.The encoder can skip the transform and apply quantization directly tothe non-transformed residual signal. The encoder can bypass bothtransform and quantization, i.e., the residual is coded directly withoutthe application of the transform or quantization processes.

The encoder decodes an encoded block to provide a reference for furtherpredictions. The quantized transform coefficients are de-quantized (140)and inverse transformed (150) to decode prediction residuals. Combining(155) the decoded prediction residuals and the predicted block, an imageblock is reconstructed. In-loop filters (165) are applied to thereconstructed picture to perform, for example, deblocking/SAO (SampleAdaptive Offset) filtering to reduce encoding artifacts. The filteredimage is stored at a reference picture buffer (180).

FIG. 13 illustrates a block diagram of a video decoder 200. In thedecoder 200, a bitstream is decoded by the decoder elements as describedbelow. Video decoder 200 generally performs a decoding pass reciprocalto the encoding pass as described in FIG. 13 . The encoder 100 alsogenerally performs video decoding as part of encoding video data.

In particular, the input of the decoder includes a video bitstream,which can be generated by video encoder 100. The bitstream is firstentropy decoded (230) to obtain transform coefficients, motion vectors,and other coded information. The picture partition information indicateshow the picture is partitioned. The decoder may therefore divide (235)the picture according to the decoded picture partitioning information.The transform coefficients are de-quantized (240) and inversetransformed (250) to decode the prediction residuals. Combining (255)the decoded prediction residuals and the predicted block, an image blockis reconstructed. The predicted block can be obtained (270) from intraprediction (260) or motion-compensated prediction (i.e., interprediction) (275). In-loop filters (265) are applied to thereconstructed image. The filtered image is stored at a reference picturebuffer (280).

The decoded picture can further go through post-decoding processing(285), for example, an inverse color transform (e.g., conversion fromYCbCr 4:2:0 to RGB 4:4:4) or an inverse remapping performing the inverseof the remapping process performed in the pre-encoding processing (101).The post-decoding processing can use metadata derived in thepre-encoding processing and signaled in the bitstream.

FIG. 14 illustrates a block diagram of an example of a system in whichvarious aspects and embodiments are implemented. System 1000 can beembodied as a device including the various components described belowand is configured to perform one or more of the aspects described inthis document. Examples of such devices, include, but are not limitedto, various electronic devices such as personal computers, laptopcomputers, smartphones, tablet computers, digital multimedia set topboxes, digital television receivers, personal video recording systems,connected home appliances, and servers. Elements of system 1000, singlyor in combination, can be embodied in a single integrated circuit (IC),multiple ICs, and/or discrete components. For example, in at least oneembodiment, the processing and encoder/decoder elements of system 1000are distributed across multiple ICs and/or discrete components. Invarious embodiments, the system 1000 is communicatively coupled to oneor more other systems, or other electronic devices, via, for example, acommunications bus or through dedicated input and/or output ports. Invarious embodiments, the system 1000 is configured to implement one ormore of the aspects described in this document.

The system 1000 includes at least one processor 1010 configured toexecute instructions loaded therein for implementing, for example, thevarious aspects described in this document. Processor 1010 can includeembedded memory, input output interface, and various other circuitriesas known in the art. The system 1000 includes at least one memory 1020(e.g., a volatile memory device, and/or a non-volatile memory device).System 1000 includes a storage device 1040, which can includenon-volatile memory and/or volatile memory, including, but not limitedto, Electrically Erasable Programmable Read-Only Memory (EEPROM),Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), RandomAccess Memory (RAM), Dynamic Random Access Memory (DRAM), Static RandomAccess Memory (SRAM), flash, magnetic disk drive, and/or optical diskdrive. The storage device 1040 can include an internal storage device,an attached storage device (including detachable and non-detachablestorage devices), and/or a network accessible storage device, asnon-limiting examples.

System 1000 includes an encoder/decoder module 1030 configured, forexample, to process data to provide an encoded video or decoded video,and the encoder/decoder module 1030 can include its own processor andmemory. The encoder/decoder module 1030 represents module(s) that can beincluded in a device to perform the encoding and/or decoding functions.As is known, a device can include one or both of the encoding anddecoding modules. Additionally, encoder/decoder module 1030 can beimplemented as a separate element of system 1000 or can be incorporatedwithin processor 1010 as a combination of hardware and software as knownto those skilled in the art.

Program code to be loaded onto processor 1010 or encoder/decoder 1030 toperform the various aspects described in this document can be stored instorage device 1040 and subsequently loaded onto memory 1020 forexecution by processor 1010. In accordance with various embodiments, oneor more of processor 1010, memory 1020, storage device 1040, andencoder/decoder module 1030 can store one or more of various itemsduring the performance of the processes described in this document. Suchstored items can include, but are not limited to, the input video, thedecoded video or portions of the decoded video, the bitstream, matrices,variables, and intermediate or final results from the processing ofequations, formulas, operations, and operational logic.

In some embodiments, memory inside of the processor 1010 and/or theencoder/decoder module 1030 is used to store instructions and to provideworking memory for processing that is needed during encoding ordecoding. In other embodiments, however, a memory external to theprocessing device (for example, the processing device can be either theprocessor 1010 or the encoder/decoder module 1030) is used for one ormore of these functions. The external memory can be the memory 1020and/or the storage device 1040, for example, a dynamic volatile memoryand/or a non-volatile flash memory. In several embodiments, an externalnon-volatile flash memory is used to store the operating system of, forexample, a television. In at least one embodiment, a fast externaldynamic volatile memory such as a RAM is used as working memory forvideo coding and decoding operations, such as for MPEG-2 (MPEG refers tothe Moving Picture Experts Group, MPEG-2 is also referred to as ISO/IEC13818, and 13818-1 is also known as H.222, and 13818-2 is also known asH.262), HEVC (HEVC refers to High Efficiency Video Coding, also known asH.265 and MPEG-H Part 2), or VVC (Versatile Video Coding, a new standardbeing developed by JVET, the Joint Video Experts Team).

The input to the elements of system 1000 can be provided through variousinput devices as indicated in block 1130. Such input devices include,but are not limited to, (i) a radio frequency (RF) portion that receivesan RF signal transmitted, for example, over the air by a broadcaster,(ii) a Component (COMP) input terminal (or a set of COMP inputterminals), (iii) a Universal Serial Bus (USB) input terminal, and/or(iv) a High Definition Multimedia Interface (HDMI) input terminal. Otherexamples, not shown in FIG. 10 , include composite video.

In various embodiments, the input devices of block 1130 have associatedrespective input processing elements as known in the art. For example,the RF portion can be associated with elements suitable for (i)selecting a desired frequency (also referred to as selecting a signal,or band-limiting a signal to a band of frequencies), (ii) downconvertingthe selected signal, (iii) band-limiting again to a narrower band offrequencies to select (for example) a signal frequency band which can bereferred to as a channel in certain embodiments, (iv) demodulating thedownconverted and band-limited signal, (v) performing error correction,and (vi) demultiplexing to select the desired stream of data packets.The RF portion of various embodiments includes one or more elements toperform these functions, for example, frequency selectors, signalselectors, band-limiters, channel selectors, filters, downconverters,demodulators, error correctors, and demultiplexers. The RF portion caninclude a tuner that performs various of these functions, including, forexample, downconverting the received signal to a lower frequency (forexample, an intermediate frequency or a near-baseband frequency) or tobaseband. In one set-top box embodiment, the RF portion and itsassociated input processing element receives an RF signal transmittedover a wired (for example, cable) medium, and performs frequencyselection by filtering, downconverting, and filtering again to a desiredfrequency band. Various embodiments rearrange the order of theabove-described (and other) elements, remove some of these elements,and/or add other elements performing similar or different functions.Adding elements can include inserting elements in between existingelements, such as, for example, inserting amplifiers and ananalog-to-digital converter. In various embodiments, the RF portionincludes an antenna.

Additionally, the USB and/or HDMI terminals can include respectiveinterface processors for connecting system 1000 to other electronicdevices across USB and/or HDMI connections. It is to be understood thatvarious aspects of input processing, for example, Reed-Solomon errorcorrection, can be implemented, for example, within a separate inputprocessing IC or within processor 1010 as necessary. Similarly, aspectsof USB or HDMI interface processing can be implemented within separateinterface ICs or within processor 1010 as necessary. The demodulated,error corrected, and demultiplexed stream is provided to variousprocessing elements, including, for example, processor 1010, andencoder/decoder 1030 operating in combination with the memory andstorage elements to process the datastream as necessary for presentationon an output device.

Various elements of system 1000 can be provided within an integratedhousing, Within the integrated housing, the various elements can beinterconnected and transmit data therebetween using suitable connectionarrangement, for example, an internal bus as known in the art, includingthe Inter-IC (12C) bus, wiring, and printed circuit boards.

The system 1000 includes communication interface 1050 that enablescommunication with other devices via communication channel 1060. Thecommunication interface 1050 can include, but is not limited to, atransceiver configured to transmit and to receive data overcommunication channel 1060. The communication interface 1050 caninclude, but is not limited to, a modem or network card and thecommunication channel 1060 can be implemented, for example, within awired and/or a wireless medium.

Data is streamed, or otherwise provided, to the system 1000, in variousembodiments, using a wireless network such as a Wi-Fi network, forexample IEEE 802.11 (IEEE refers to the Institute of Electrical andElectronics Engineers). The Wi-Fi signal of these embodiments isreceived over the communications channel 1060 and the communicationsinterface 1050 which are adapted for Wi-Fi communications. Thecommunications channel 1060 of these embodiments is typically connectedto an access point or router that provides access to external networksincluding the Internet for allowing streaming applications and otherover-the-top communications. Other embodiments provide streamed data tothe system 1000 using a set-top box that delivers the data over the HDMIconnection of the input block 1130. Still other embodiments providestreamed data to the system 1000 using the RF connection of the inputblock 1130. As indicated above, various embodiments provide data in anon-streaming manner. Additionally, various embodiments use wirelessnetworks other than Wi-Fi, for example a cellular network or a Bluetoothnetwork.

The system 1000 can provide an output signal to various output devices,including a display 1100, speakers 1110, and other peripheral devices1120. The display 1100 of various embodiments includes one or more of,for example, a touchscreen display, an organic light-emitting diode(OLED) display, a curved display, and/or a foldable display. The display1100 can be for a television, a tablet, a laptop, a cell phone (mobilephone), or other device. The display 1100 can also be integrated withother components (for example, as in a smart phone), or separate (forexample, an external monitor for a laptop). The other peripheral devices1120 include, in various examples of embodiments, one or more of astand-alone digital video disc (or digital versatile disc) (DVR, forboth terms), a disk player, a stereo system, and/or a lighting system.Various embodiments use one or more peripheral devices 1120 that providea function based on the output of the system 1000. For example, a diskplayer performs the function of playing the output of the system 1000.

In various embodiments, control signals are communicated between thesystem 1000 and the display 1100, speakers 1110, or other peripheraldevices 1120 using signaling such as AV.Link, Consumer ElectronicsControl (CEC), or other communications protocols that enabledevice-to-device control with or without user intervention. The outputdevices can be communicatively coupled to system 1000 via dedicatedconnections through respective interfaces 1070, 1080, and 1090.Alternatively, the output devices can be connected to system 1000 usingthe communications channel 1060 via the communications interface 1050.The display 1100 and speakers 1110 can be integrated in a single unitwith the other components of system 1000 in an electronic device suchas, for example, a television. In various embodiments, the displayinterface 1070 includes a display driver, such as, for example, a timingcontroller (T Con) chip.

The display 1100 and speaker 1110 can alternatively be separate from oneor more of the other components, for example, if the RF portion of input1130 is part of a separate set-top box. In various embodiments in whichthe display 1100 and speakers 1110 are external components, the outputsignal can be provided via dedicated output connections, including, forexample, HDMI ports, USB ports, or COMP outputs.

The embodiments can be carried out by computer software implemented bythe processor 1010 or by hardware, or by a combination of hardware andsoftware. As a non-limiting example, the embodiments can be implementedby one or more integrated circuits. The memory 1020 can be of any typeappropriate to the technical environment and can be implemented usingany appropriate data storage technology, such as optical memory devices,magnetic memory devices, semiconductor-based memory devices, fixedmemory, and removable memory, as non-limiting examples. The processor1010 can be of any type appropriate to the technical environment, andcan encompass one or more of microprocessors, general purpose computers,special purpose computers, and processors based on a multi-corearchitecture, as non-limiting examples.

Various implementations involve decoding. “Decoding”, as used in thisapplication, can encompass all or part of the processes performed, forexample, on a received encoded sequence in order to produce a finaloutput suitable for display. In various embodiments, such processesinclude one or more of the processes typically performed by a decoder,for example, entropy decoding, inverse quantization, inversetransformation, and differential decoding. In various embodiments, suchprocesses also, or alternatively, include processes performed by adecoder of various implementations described in this application, forexample, decoding a bi-prediction flag, decoding a partition forbi-prediction and index in a predictor list, determining a weightaccording to the position of the pixel in the block, in particular alongthe edge of a partition of the PU and performing motion compensation ininter using bi-prediction and determined weight.

As further examples, in one embodiment “decoding” refers only to entropydecoding, in another embodiment “decoding” refers only to differentialdecoding, and in another embodiment “decoding” refers to a combinationof entropy decoding and differential decoding. Whether the phrase“decoding process” is intended to refer specifically to a subset ofoperations or generally to the broader decoding process will be clearbased on the context of the specific descriptions and is believed to bewell understood by those skilled in the art.

Various implementations involve encoding. In an analogous way to theabove discussion about “decoding”, “encoding” as used in thisapplication can encompass all or part of the processes performed, forexample, on an input video sequence in order to produce an encodedbitstream. In various embodiments, such processes include one or more ofthe processes typically performed by an encoder, for example,partitioning, differential encoding, transformation, quantization, andentropy encoding. In various embodiments, such processes also, oralternatively, include processes performed by an encoder of variousimplementations described in this application, for example, determininga predictor in a bi-prediction scheme using motion compensation andmotion prediction, wherein the weight of the bi-prediction is based onthe position of the pixel in the block, in particular along the edge ofa partition of the PU and performing motion compensation in inter usingbi-prediction and, encoding a bi-prediction flag, encoding a partitionfor bi-prediction and encoding index in a predictor list.

As further examples, in one embodiment “encoding” refers only to entropyencoding, in another embodiment “encoding” refers only to differentialencoding, and in another embodiment “encoding” refers to a combinationof differential encoding and entropy encoding. Whether the phrase“encoding process” is intended to refer specifically to a subset ofoperations or generally to the broader encoding process will be clearbased on the context of the specific descriptions and is believed to bewell understood by those skilled in the art.

Note that the syntax elements as used herein, for example, diagonal_dir,diagonal_pos, diagonal_flag, partition_dir, partition_pos, aredescriptive terms. As such, they do not preclude the use of other syntaxelement names.

When a figure is presented as a flow diagram, it should be understoodthat it also provides a block diagram of a corresponding apparatus.Similarly, when a figure is presented as a block diagram, it should beunderstood that it also provides a flow diagram of a correspondingmethod/process.

Various embodiments refer to rate distortion optimization for instancewhen testing combinations for the bi-pred multiple partition PUs at theencoder. In particular, during the encoding process, the balance ortrade-off between the rate and distortion is usually considered, oftengiven the constraints of computational complexity. The rate distortionoptimization is usually formulated as minimizing a rate distortionfunction, which is a weighted sum of the rate and of the distortion.There are different approaches to solve the rate distortion optimizationproblem. For example, the approaches may be based on an extensivetesting of all encoding options, including all considered modes orcoding parameters values, with a complete evaluation of their codingcost and related distortion of the reconstructed signal after coding anddecoding. Faster approaches may also be used, to save encodingcomplexity, in particular with computation of an approximated distortionbased on the prediction or the prediction residual signal, not thereconstructed one. Mix of these two approaches can also be used, such asby using an approximated distortion for only some of the possibleencoding options, and a complete distortion for other encoding options.Other approaches only evaluate a subset of the possible encodingoptions. More generally, many approaches employ any of a variety oftechniques to perform the optimization, but the optimization is notnecessarily a complete evaluation of both the coding cost and relateddistortion.

The implementations and aspects described herein can be implemented in,for example, a method or a process, an apparatus, a software program, adata stream, or a signal. Even if only discussed in the context of asingle form of implementation (for example, discussed only as a method),the implementation of features discussed can also be implemented inother forms (for example, an apparatus or program). An apparatus can beimplemented in, for example, appropriate hardware, software, andfirmware. The methods can be implemented in, for example, a processor,which refers to processing devices in general, including, for example, acomputer, a microprocessor, an integrated circuit, or a programmablelogic device. Processors also include communication devices, such as,for example, computers, cell phones, portable/personal digitalassistants (“PDAs”), and other devices that facilitate communication ofinformation between end-users.

Reference to “one embodiment” or “an embodiment” or “one implementation”or “an implementation”, as well as other variations thereof, means thata particular feature, structure, characteristic, and so forth describedin connection with the embodiment is included in at least oneembodiment. Thus, the appearances of the phrase “in one embodiment” or“in an embodiment” or “in one implementation” or “in an implementation”,as well any other variations, appearing in various places throughoutthis application are not necessarily all referring to the sameembodiment.

Additionally, this application may refer to “determining” various piecesof information. Determining the information can include one or more of,for example, estimating the information, calculating the information,predicting the information, or retrieving the information from memory.

Further, this application may refer to “accessing” various pieces ofinformation. Accessing the information can include one or more of, forexample, receiving the information, retrieving the information (forexample, from memory), storing the information, moving the information,copying the information, calculating the information, determining theinformation, predicting the information, or estimating the information.

Additionally, this application may refer to “receiving” various piecesof information. Receiving is, as with “accessing”, intended to be abroad term. Receiving the information can include one or more of, forexample, accessing the information, or retrieving the information (forexample, from memory). Further, “receiving” is typically involved, inone way or another, during operations such as, for example, storing theinformation, processing the information, transmitting the information,moving the information, copying the information, erasing theinformation, calculating the information, determining the information,predicting the information, or estimating the information.

It is to be appreciated that the use of any of the following “/”,“and/or”, and “at least one of”, for example, in the cases of “A/B”, “Aand/or B” and “at least one of A and B”, is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of both options (A andB). As a further example, in the cases of “A, B, and/or C” and “at leastone of A, B, and C”, such phrasing is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of the third listedoption (C) only, or the selection of the first and the second listedoptions (A and B) only, or the selection of the first and third listedoptions (A and C) only, or the selection of the second and third listedoptions (B and C) only, or the selection of all three options (A and Band C). This may be extended, as is clear to one of ordinary skill inthis and related arts, for as many items as are listed.

Also, as used herein, the word “signal” refers to, among other things,indicating something to a corresponding decoder. For example, in certainembodiments the encoder signals a particular one of a plurality ofparameters for improved bi-prediction, for instance for signaling thepartition of a block and associated weight. In this way, in anembodiment the same parameter is used at both the encoder side and thedecoder side. Thus, for example, an encoder can transmit (explicitsignaling) a particular parameter to the decoder so that the decoder canuse the same particular parameter. Conversely, if the decoder alreadyhas the particular parameter as well as others, then signaling can beused without transmitting (implicit signaling) to simply allow thedecoder to know and select the particular parameter. By avoidingtransmission of any actual functions, a bit savings is realized invarious embodiments. It is to be appreciated that signaling can beaccomplished in a variety of ways. For example, one or more syntaxelements, flags, and so forth are used to signal information to acorresponding decoder in various embodiments. While the precedingrelates to the verb form of the word “signal”, the word “signal” canalso be used herein as a noun.

As will be evident to one of ordinary skill in the art, implementationscan produce a variety of signals formatted to carry information that canbe, for example, stored or transmitted. The information can include, forexample, instructions for performing a method, or data produced by oneof the described implementations. For example, a signal can be formattedto carry the bitstream of a described embodiment. Such a signal can beformatted, for example, as an electromagnetic wave (for example, using aradio frequency portion of spectrum) or as a baseband signal. Theformatting can include, for example, encoding a data stream andmodulating a carrier with the encoded data stream. The information thatthe signal carries can be, for example, analog or digital information.The signal can be transmitted over a variety of different wired orwireless links, as is known. The signal can be stored on aprocessor-readable medium.

We describe a number of embodiments. Features of these embodiments canbe provided alone or in any combination. Further, embodiments caninclude one or more of the following features, devices, or aspects,alone or in any combination, across various claim categories and types:

-   Modifying the bi-prediction process applied in the decoder and/or    encoder.-   Applying bi-prediction methods with increased precision in the    decoder and/or encoder.-   Enabling several weights in a same PU for bi-prediction methods in    the decoder and/or encoder.-   Determining weights in a PU for bi-prediction methods according to    the position of the pixel with regard to the edge of a partition of    the PU in the decoder and/or encoder.-   Determining weights in a PU for bi-prediction methods according to    the position of the pixel with regard to the edge of multiples    partitions of the PU in the decoder and/or encoder.-   Inserting in the signaling, syntax elements that enable the decoder    to identify the PU partition for bi-prediction method to use, and    optionally the weight for each pixels.-   Selecting, based on these syntax elements, the partition and the    weights for the bi-prediction method to apply at the decoder.-   Using uni-prediction motion model to combine them into weighted    bi-prediction at encoder and/or decoder according to any of the    embodiments discussed.-   A bitstream or signal that includes one or more of the described    syntax elements, or variations thereof.-   Inserting in the signaling syntax elements that enable the decoder    to perform motion compensation in a manner corresponding to that    used by an encoder.-   Creating and/or transmitting and/or receiving and/or decoding a    bitstream or signal that includes one or more of the described    syntax elements, or variations thereof.-   A TV, set-top box, cell phone, tablet, or other electronic device    that performs bi-prediction in Inter according to any of the    embodiments described.-   A TV, set-top box, cell phone, tablet, or other electronic device    that bi-prediction in Inter according to any of the embodiments    described, and that displays (e.g., using a monitor, screen, or    other type of display) a resulting image.-   A TV, set-top box, cell phone, tablet, or other electronic device    that tunes (e.g., using a tuner) a channel to receive a signal    including an encoded image, and performs bi-prediction in Inter    according to any of the embodiments described.-   A TV, set-top box, cell phone, tablet, or other electronic device    that receives (e.g., using an antenna) a signal over the air that    includes an encoded image, and performs bi-prediction in Inter    parameters according to any of the embodiments described.

1. A method, comprising: obtaining a first information indicating asplitting of a block of a picture with a geometric partition; obtaininga second information indicating a direction of an edge with thegeometric partition; obtaining a third information indicating a positionof an edge with the geometric partition; obtaining, from uni-prediction,a first predictor for the block of the picture using a first referencepicture; obtaining, from uni-prediction, a second predictor for theblock of the picture using a second reference picture; obtaining aweighted average of the first predictor and the second predictor;wherein a sample of the weighted average is obtained by applying a firstweight to a sample of the first predictor and by applying a secondweight to a co-located sample of the second predictor, wherein the firstweight and the second weight are responsive to the first information,second information, the third information and to a position of thesample in the block; obtaining a third predictor for the block byshifting and clipping the weighted average; and decoding the block ofthe picture using the third predictor generated by a geometric partitionmode.
 2. The method of claim 1, wherein the first predictor is obtainedfor at least a first part of the block; and the second predictor isobtained for at least a second part of the block.
 3. The method of claim1, the second information indicating a direction of an edge with thegeometric partition is an index coding at least 3 different angles forthe edge.
 4. The method of claim 1, the third information indicating aposition of an edge with the geometric partition is an index coding atleast 3 different distances from the edge to a reference sample of theblock.
 5. The method of claim 1, wherein the first weight and the secondweight depend on a distance between the sample and an edge of thegeometric partition of the block, wherein a position of the edge isderived from the first information and the second information.
 6. Themethod of claim 5, wherein the block of the picture comprises a lumacomponent and two chroma components and wherein the first weight and thesecond weight further depend on the luma component or chroma component.7. An apparatus, comprising: one or more processors, wherein the one ormore processors are configured to: obtain a first information indicatinga splitting of a block of a picture with a geometric partition; obtain asecond information indicating a direction of an edge with the geometricpartition; obtain a third information indicating a position of an edgewith the geometric partition; obtain, from uni-prediction, a firstpredictor for the block of the picture using a first reference picture;obtain, from uni-prediction, a second predictor for the block of thepicture using a second reference picture; obtain a weighted average ofthe first predictor and the second predictor; wherein a sample of theweighted average is obtained by applying a first weight to a sample ofthe first predictor and by applying a second weight to a co-locatedsample of the second predictor, wherein the first weight and the secondweight are responsive to the first information, second information, thethird information and to a position of the sample in the block; obtain athird predictor for the block by shifting and clipping the weightedaverage; and decode the block of the picture using the third predictorgenerated by a geometric partition mode.
 8. The apparatus of claim 7,wherein the first predictor is obtained for at least a first part of theblock; and the second predictor is obtained for at least a second partof the block.
 9. The apparatus of claim 7, the second informationindicating a direction of an edge with the geometric partition is anindex coding at least 3 different angles for the edge.
 10. The apparatusof claim 7, the third information indicating a position of an edge withthe geometric partition is an index coding at least 3 differentdistances from the edge to a reference sample of the block.
 11. Theapparatus of claim 7, wherein the first weight and the second weightdepend on a distance between the sample and an edge of the geometricpartition of the block, wherein a position of the edge is derived fromthe first information and the second information.
 12. The apparatus ofclaim 11, wherein the block of the picture comprises a luma componentand two chroma components and wherein the first weight and the secondweight further depend on the luma component or chroma component.
 13. Amethod, comprising: obtaining a first information indicating a splittingof a block of a picture with a geometric partition; obtaining a secondinformation indicating a direction of an edge with the geometricpartition; obtaining a third information indicating a position of anedge with the geometric partition; obtaining, from uni-prediction, afirst predictor for the block of the picture using a first referencepicture; obtaining, from uni-prediction, a second predictor for theblock of the picture using a second reference picture; obtaining aweighted average of the first predictor and the second predictor;wherein a sample of the weighted average is obtained by applying a firstweight to a sample of the first predictor and by applying a secondweight to a co-located sample of the second predictor, wherein the firstweight and the second weight are responsive to the first information,second information, the third information and to a position of thesample in the block; obtaining a third predictor for the block byshifting and clipping the weighted average; and encoding the block ofthe picture using the third predictor generated by a geometric partitionmode.
 14. The method of claim 13, wherein the first predictor isobtained for at least a first part of the block; and the secondpredictor is obtained for at least a second part of the block.
 15. Themethod of claim 13, the second information indicating a direction of anedge with the geometric partition is an index coding at least 3different angles for the edge.
 16. The method of claim 13, the thirdinformation indicating a position of an edge with the geometricpartition is an index coding at least 3 different distances from theedge to a reference sample of the block.
 17. The method of claim 13,wherein the first weight and the second weight depend on a distancebetween the sample and an edge of the geometric partition of the block,wherein a position of the edge is derived from the first information andthe second information.
 18. The method of claim 17, wherein the block ofthe picture comprises a luma component and two chroma components andwherein the first weight and the second weight further depend on theluma component or chroma component.
 19. An apparatus, comprising: one ormore processors, wherein the one or more processors are configured to:obtain a first information indicating a splitting of a block of apicture with a geometric partition; obtain a second informationindicating a direction of an edge with the geometric partition; obtain athird information indicating a position of an edge with the geometricpartition; obtain, from uni-prediction, a first predictor for the blockof the picture using a first reference picture; obtain, fromuni-prediction, a second predictor for the block of the picture using asecond reference picture; obtain a weighted average of the firstpredictor and the second predictor; wherein a sample of the weightedaverage is obtained by applying a first weight to a sample of the firstpredictor and by applying a second weight to a co-located sample of thesecond predictor, wherein the first weight and the second weight areresponsive to the first information, second information, the thirdinformation and to a position of the sample in the block; obtain a thirdpredictor for the block by shifting and clipping the weighted average;and encode the block of the picture using the third predictor generatedby a geometric partition mode.
 20. The apparatus of claim 19, whereinthe first predictor is obtained for at least a first part of the block;and the second predictor is obtained for at least a second part of theblock.
 21. The apparatus of claim 19, the second information indicatinga direction of an edge with the geometric partition is an index codingat least 3 different angles for the edge.
 22. The apparatus of claim 19,the third information indicating a position of an edge with thegeometric partition is an index coding at least 3 different distancesfrom the edge to a reference sample of the block.
 23. The apparatus ofclaim 19, wherein the first weight and the second weight depend on adistance between the sample and an edge of the geometric partition ofthe block, wherein a position of the edge is derived from the firstinformation and the second information.
 24. The apparatus of claim 23,wherein the block of the picture comprises a luma component and twochroma components and wherein the first weight and the second weightfurther depend on the luma component or chroma component.